The Sapienza computer scientists say Wi-Fi signals offer superior surveillance potential compared to cameras because they're not affected by light conditions, can penetrate walls and other obstacles, and they're more privacy-preserving than visual images.

[…] The Rome-based researchers who proposed WhoFi claim their technique makes accurate matches on the public NTU-Fi dataset up to 95.5 percent of the time when the deep neural network uses the transformer encoding architecture.

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[–] 1 point 1 year ago (4 children)

They can see you're a person but not exactly who you are.

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  • [–] -1 points 1 year ago (3 children)
  • [–] 2 points 1 year ago* (2 children)

    Well they can identify you are the same person but not your identity.. So it's like a disenbodied fingerprint.

    I suppose they could potentially make some database and train an AI on it someday to match to actual identities, but usefulness would be pretty limited at only 95% accuracy. That's a false reading 1/20 times, so I suspect it would fail bigly to accurately recognize people from large data sets.

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